TINAGL1 Human, Sf9

What is TINAGL1 and what are its primary functions in human biology?

TINAGL1 (Tubulointerstitial Nephritis Antigen-Like 1) is a secreted protein that functions in cell-matrix interactions and has been implicated in various biological processes. In normal physiology, TINAGL1 mediates cell adhesion and migration through interaction with integrins. Recent research has demonstrated that TINAGL1 plays significant roles in tumor microenvironments, particularly in cancer-associated fibroblasts (CAFs). It enhances the phosphorylation of focal adhesion kinase (FAK) and promotes mesenchymal marker expression in cancer cells .

Why is the Sf9-expressed recombinant TINAGL1 protein important for research applications?

Recombinant Human TINAGL1 protein expressed in Sf9 insect cells provides researchers with a consistent source of the protein for functional studies. The Sf9 expression system allows for proper folding and post-translational modifications that may be critical for protein function, while still yielding sufficient quantities for experimental use . Unlike bacterial expression systems, insect cell-based systems like Sf9 offer eukaryotic processing pathways that can produce proteins more similar to their native human counterparts, making them valuable for studying protein-protein interactions, enzymatic activities, and for use in structural studies.

What is the molecular weight and structure of human TINAGL1 protein?

Human TINAGL1 is a glycoprotein with a molecular weight of approximately 52-53 kDa. The protein contains several functional domains including:

• An N-terminal signal peptide

• A cysteine-rich domain

• A follistatin-like domain

• A calcium-binding EGF-like domain

These structural features enable TINAGL1 to interact with various extracellular matrix components and cell surface receptors, particularly integrins that mediate its cellular effects .

What are the optimal storage and handling conditions for recombinant TINAGL1 Sf9 protein?

For optimal stability and activity retention of recombinant human TINAGL1 expressed in Sf9 cells:

• Store lyophilized protein at -20°C to -80°C

• After reconstitution, aliquot and store at -80°C to avoid repeated freeze-thaw cycles

• For short-term use (less than 1 week), store at 4°C

• Avoid multiple freeze-thaw cycles which can cause protein denaturation and activity loss

• Use sterile techniques when handling the protein to prevent contamination

• Reconstitute only in recommended buffers (typically PBS or similar physiological buffers)

How can I validate the biological activity of recombinant TINAGL1?

Biological activity validation of recombinant TINAGL1 can be performed through several established methodologies:

• Cell adhesion assays: Test the ability of TINAGL1 to promote adhesion of relevant cell types (epithelial cells or fibroblasts) when coated on culture surfaces.

• Cell migration assays: Use transwell or wound healing assays to assess TINAGL1's effect on cell migration, particularly with cancer cells like those from diffuse-type gastric cancer (DGC).

• FAK phosphorylation analysis: Measure phosphorylation of focal adhesion kinase (Y397) by Western blotting after treating cells with TINAGL1, as this is a key downstream signaling event.

• Integrin binding assays: Assess direct binding to integrin beta 1 using co-immunoprecipitation or surface plasmon resonance.

• Functional assays in cancer models: Evaluate effects on tumorigenesis using soft agar colony formation assays or in vivo models .

What cell types are most appropriate for studying TINAGL1 function?

Based on current research, the following cell types are particularly relevant for TINAGL1 functional studies:

• Cancer-associated fibroblasts (CAFs): These cells naturally express high levels of TINAGL1 and represent a physiologically relevant model.

• Diffuse-type gastric cancer cells: These cancer cells respond to TINAGL1 through increased migration and enhanced FAK phosphorylation.

• Normal fibroblasts: Serve as important controls when comparing to CAFs.

• Epithelial cancer cell lines: Useful for studying TINAGL1's effects on epithelial-mesenchymal transition.

When selecting cell models, consider the research question's specific context, as TINAGL1's effects may vary between different tissue origins and disease states .

How does TINAGL1 from CAFs contribute to cancer progression mechanisms?

TINAGL1 secreted by cancer-associated fibroblasts (CAFs) promotes cancer progression through several interconnected mechanisms:

• Enhanced FAK phosphorylation: TINAGL1 secreted by CAFs induces phosphorylation of focal adhesion kinase in cancer cells, particularly in diffuse-type gastric cancer (DGC). This activation leads to downstream signaling that supports cancer cell migration and invasion.

• Mesenchymal marker induction: Exposure to CAF-derived TINAGL1 enhances the expression of mesenchymal markers in cancer cells, potentially promoting epithelial-mesenchymal transition.

• Integrin signaling: TINAGL1 interacts with integrin beta 1 on cancer cells to transduce signals that promote migration and invasion.

• In vivo effects: In animal models, co-injection of CAFs with DGC cells resulted in more aggressive tumor phenotypes, including increased lymph node metastasis. This effect appears to be mediated, at least in part, by TINAGL1 .

These findings suggest that targeting TINAGL1 in the tumor microenvironment could be a viable therapeutic strategy for cancers where CAFs play a prominent role.

What are the technical challenges in studying TINAGL1-integrin interactions?

Researchers studying TINAGL1-integrin interactions face several technical challenges:

• Protein conformation: TINAGL1's interaction with integrins may depend on specific conformational states that can be difficult to maintain in recombinant proteins.

• Co-factor requirements: The interaction may require calcium ions or other co-factors that need to be precisely controlled in experimental settings.

• Binding specificity: TINAGL1 may interact with multiple integrin heterodimers with different affinities, necessitating careful experimental design to distinguish specific from non-specific interactions.

• Functional redundancy: Other secreted proteins in the cellular microenvironment may have overlapping functions with TINAGL1, complicating interpretation of results.

• Context-dependent effects: TINAGL1's effects may vary depending on the specific cellular context and the presence of other extracellular matrix components .

Addressing these challenges requires careful experimental design, appropriate controls, and complementary approaches combining biochemical, cellular, and in vivo methodologies.

How can TINAGL1 expression be effectively knocked down or inhibited in research models?

Several approaches can be used to effectively inhibit TINAGL1 in research models:

• RNA interference:

  • siRNA: For transient knockdown in cell culture models. Has been validated in CAFs to reduce TINAGL1 expression, with corresponding reductions in cancer cell migration .

  • shRNA: For stable knockdown in long-term experiments or in vivo studies. Has been used successfully to demonstrate reduced FAK phosphorylation in cancer cells when TINAGL1 is knocked down in CAFs .

• CRISPR-Cas9 gene editing:

  • Can be used to generate complete TINAGL1 knockout cell lines or animal models for studying loss-of-function phenotypes.

• Neutralizing antibodies:

  • Anti-TINAGL1 antibodies can be used to block the protein's interaction with its receptors in culture media or in vivo.

• Recombinant decoy receptors:

  • Soluble forms of integrin beta 1 could potentially sequester TINAGL1 and prevent its interaction with cellular receptors.

When designing inhibition studies, it's important to validate knockdown or inhibition efficiency using both RNA (qRT-PCR) and protein (Western blot) detection methods .

What is the prognostic significance of TINAGL1 expression in cancer patients?

The prognostic significance of TINAGL1 in cancer has been documented in several studies:

The consistent association between high TINAGL1 expression and poor clinical outcomes suggests its potential value as a prognostic biomarker in certain cancer types, particularly those characterized by significant stromal involvement .

How might targeting TINAGL1 be developed as a therapeutic strategy?

Targeting TINAGL1 as a therapeutic strategy could be developed through several approaches:

• Neutralizing antibodies: Development of antibodies specifically targeting TINAGL1 to prevent its interaction with receptors on cancer cells. This approach would directly target the protein in the tumor microenvironment.

• Small molecule inhibitors: Design of compounds that could disrupt the TINAGL1-integrin interaction or inhibit downstream signaling pathways, such as FAK phosphorylation.

• CAF-targeted therapies: Since CAFs are the major source of TINAGL1 in tumors, strategies that selectively target or reprogram CAFs could indirectly reduce TINAGL1's effects.

• Gene therapy approaches: Localized delivery of siRNA or similar technologies to reduce TINAGL1 expression specifically in the tumor microenvironment.

The potential for targeting TINAGL1 is supported by experimental evidence showing that blocking TINAGL1 in CAFs reduced phosphorylation of FAK and migration of cancer cells. This suggests that disrupting the TINAGL1-mediated communication between CAFs and cancer cells could be a viable approach to inhibit tumor progression .

What methodologies can be used to detect TINAGL1 expression in patient tissues?

Several complementary methodologies can be used to detect TINAGL1 expression in patient tissues:

• RNA in-situ hybridization (RNA-ISH):

  • Allows detection of TINAGL1 mRNA directly in tissue sections

  • Useful for formalin-fixed, paraffin-embedded (FFPE) tissues

  • Preserves spatial context within the tissue architecture

• Immunohistochemistry (IHC):

  • Detects TINAGL1 protein expression in tissue sections

  • Can reveal subcellular localization and distribution within different tissue compartments

  • Works on both frozen and FFPE tissues with appropriate antibodies

• Quantitative RT-PCR:

  • Provides quantitative measurement of TINAGL1 mRNA levels

  • Useful for comparing expression levels between different samples

  • Requires extraction of RNA from tissue samples

• Western blotting:

  • Confirms specificity of antibodies

  • Provides semi-quantitative information about protein levels

  • Requires protein extraction from tissues

• Multiplex staining approaches:

  • Allows co-localization studies with other markers (e.g., COL1A1)

  • Helps identify the specific cell types expressing TINAGL1

These methods can be used individually or in combination to comprehensively assess TINAGL1 expression patterns in clinical samples.

What are the potential research opportunities for understanding TINAGL1's role in non-cancer conditions?

While TINAGL1 has been primarily studied in cancer contexts, several promising research opportunities exist for investigating its role in non-cancer conditions:

• Fibrotic disorders: Given TINAGL1's association with fibroblasts and extracellular matrix components, its potential role in fibrotic conditions affecting the kidney, liver, lung, or other organs warrants investigation.

• Inflammatory diseases: TINAGL1's potential involvement in modulating inflammatory responses through its interaction with immune cells could be explored.

• Wound healing and tissue repair: The protein's role in cellular migration and adhesion suggests it may have functions in normal wound healing processes.

• Developmental biology: Investigation of TINAGL1's expression patterns and functions during embryonic development could reveal previously unknown roles.

• Cardiovascular diseases: Given the importance of cell-matrix interactions in vascular biology, TINAGL1 might have functions in vascular remodeling or atherosclerosis.

These research directions would benefit from initial expression profiling across different tissues and disease states, followed by functional studies in appropriate model systems.

How might integrating TINAGL1 research with emerging technologies advance our understanding?

Integration of TINAGL1 research with emerging technologies could significantly advance our understanding in several ways:

• Single-cell RNA sequencing: Could reveal cell-specific expression patterns of TINAGL1 and its receptors within heterogeneous tissues, particularly within the tumor microenvironment.

• Spatial transcriptomics/proteomics: Would provide information about the spatial distribution of TINAGL1 in relation to other molecules and cell types in tissues.

• CRISPR-based functional genomics: Genome-wide screens could identify synthetic lethal interactions with TINAGL1 or reveal previously unknown regulatory mechanisms.

• Organoid and 3D culture systems: Would allow study of TINAGL1 function in more physiologically relevant contexts that recapitulate tissue architecture.

• Proteomics and interactomics: Could identify novel binding partners and signaling pathways associated with TINAGL1.

• In vivo imaging techniques: Development of probes for non-invasive visualization of TINAGL1 expression or activity could facilitate translational research.

• AI/machine learning approaches: Could help integrate multi-omics data to identify patterns and generate hypotheses about TINAGL1's roles in complex biological systems.

These technological approaches would complement traditional biochemical and cell biological methods to provide a more comprehensive understanding of TINAGL1's functions.

What are the major knowledge gaps in our understanding of TINAGL1 structure-function relationships?

Several significant knowledge gaps exist in our understanding of TINAGL1 structure-function relationships:

• Complete three-dimensional structure: The detailed crystal structure of full-length TINAGL1 has not been determined, limiting our understanding of how its different domains interact and function.

• Binding interfaces: The specific amino acid residues involved in TINAGL1's interaction with integrin beta 1 and other potential receptors remain incompletely characterized.

• Post-translational modifications: The impact of glycosylation and other modifications on TINAGL1's function has not been fully explored.

• Conformational dynamics: How TINAGL1's structure changes upon binding to different partners and how this influences its signaling outcomes remains poorly understood.

• Structure-based drug design opportunities: Without detailed structural information, the rational design of inhibitors targeting TINAGL1 or its interactions is challenging.

• Regulation of secretion: The mechanisms controlling TINAGL1 secretion from cells, especially in pathological contexts like cancer, are not well characterized.

Addressing these gaps would likely require interdisciplinary approaches combining structural biology, biochemistry, cell biology, and computational modeling.

What are the key considerations when designing experiments to study TINAGL1-mediated signaling pathways?

When designing experiments to study TINAGL1-mediated signaling pathways, researchers should consider:

• Cell type selection: Choose relevant cell types that express appropriate receptors for TINAGL1, such as those expressing integrin beta 1. Both producer cells (e.g., CAFs) and responder cells (e.g., cancer cells) should be considered in co-culture experiments.

• Concentration and timing: Determine physiologically relevant concentrations of TINAGL1 based on literature or preliminary experiments. Consider both acute and chronic exposure timelines.

• Pathway analysis breadth: Examine multiple potential downstream pathways beyond FAK, including other integrin-associated pathways, MAPK/ERK signaling, and PI3K/AKT pathways.

• Controls and validation:

  • Use multiple siRNAs or shRNAs targeting different regions of TINAGL1 to control for off-target effects

  • Include both positive controls (known activators of the pathways) and negative controls

  • Validate key findings using complementary approaches (e.g., both protein overexpression and knockdown)

• Spatial and temporal dynamics: Consider using live-cell imaging approaches to capture the spatial and temporal dynamics of signaling events triggered by TINAGL1.

• Pathway crosstalk: Investigate potential crosstalk between TINAGL1-initiated signaling and other pathways relevant to the cell type and biological context .

How can researchers distinguish between direct and indirect effects of TINAGL1 in biological systems?

Distinguishing between direct and indirect effects of TINAGL1 requires careful experimental design:

• Purified protein interactions: Use purified recombinant TINAGL1 and potential interacting partners in direct binding assays (e.g., surface plasmon resonance, ELISA) to establish direct molecular interactions.

• Domain mapping and mutagenesis: Create mutants of TINAGL1 with altered binding sites to determine if specific interactions are required for observed effects.

• Rapid response assays: Measure immediate signaling events (seconds to minutes) following TINAGL1 addition, which are more likely to represent direct effects than changes observed after hours or days.

• Proximity labeling approaches: Use BioID or APEX2-based approaches to identify proteins in close proximity to TINAGL1 in living cells.

• Receptor blocking: Use blocking antibodies or soluble receptor fragments to inhibit specific interactions and determine if they are required for TINAGL1's effects.

• Kinetics analysis: Compare the kinetics of different cellular responses to establish likely cause-effect relationships.

• Conditioned media controls: When studying secreted TINAGL1, use immunodepletion of TINAGL1 from conditioned media to confirm specificity of observed effects .

What are the optimal approaches for quantifying TINAGL1 protein in different sample types?

Optimal approaches for quantifying TINAGL1 protein vary depending on the sample type:

For cell culture media and biological fluids:

• Enzyme-Linked Immunosorbent Assay (ELISA):

  • Provides quantitative measurement of soluble TINAGL1

  • High sensitivity and specificity when validated antibodies are used

  • Suitable for high-throughput analysis of multiple samples

• Western blotting with quantitative detection:

  • Semi-quantitative approach using standard curves

  • Confirms protein size and potential processing forms

  • Less sensitive than ELISA but provides additional information about protein processing

For tissue samples:

• Immunohistochemistry with digital image analysis:

  • Allows quantification of staining intensity while preserving spatial information

  • Can distinguish TINAGL1 expression in different cellular compartments

  • Enables correlation with histopathological features

• Multiplexed protein analysis:

  • Mass spectrometry-based approaches for unbiased protein quantification

  • Can detect TINAGL1 along with other proteins in the same sample

  • Requires specialized equipment but provides comprehensive data

For all sample types:

• Include appropriate positive and negative controls

• Validate antibody specificity using TINAGL1 knockdown or knockout samples

• Consider using multiple detection methods for confirmation of key findings

• Include standard curves with recombinant protein for absolute quantification

How conserved is TINAGL1 across species, and what can we learn from animal models?

TINAGL1 demonstrates notable evolutionary conservation across vertebrate species, providing valuable insights through comparative biology:

• Sequence conservation:

  • Human TINAGL1 shares approximately 90% amino acid identity with mouse and rat orthologs

  • Functional domains show particularly high conservation, suggesting evolutionary pressure to maintain specific functions

  • Lower vertebrates (fish, amphibians) also possess recognizable TINAGL1 orthologs with conserved domain architecture

• Expression patterns:

  • Similar tissue distribution patterns are observed across mammalian species

  • Developmental expression patterns are also generally conserved

• Lessons from animal models:

  • Mouse models have demonstrated roles for TINAGL1 in development and tissue homeostasis

  • Knockout mouse studies can reveal phenotypes not evident from cell culture systems

  • Mouse models of cancer have confirmed the role of TINAGL1 in tumor progression, supporting findings from human studies

• Cross-species functionality:

  • Human TINAGL1 is often functional in other mammalian systems, facilitating research using recombinant human protein in animal models

  • This conservation supports the translational relevance of findings from model organisms

Understanding the evolutionary conservation of TINAGL1 helps establish which aspects of its biology are fundamental across species versus those that might be species-specific .

How do recombinant TINAGL1 proteins produced in different expression systems compare?

Recombinant TINAGL1 proteins produced in different expression systems show important differences that researchers should consider when selecting reagents:

The choice of expression system should be guided by the specific research application. For studies focusing on TINAGL1's interaction with integrins and downstream signaling, insect cell (Sf9) or mammalian cell-derived proteins are generally preferred due to their superior folding and modification .

What alternative or complementary proteins to TINAGL1 should researchers consider in their experimental designs?

Researchers studying TINAGL1 should consider several alternative or complementary proteins in their experimental designs:

• Related family members:

  • TINAG (Tubulointerstitial Nephritis Antigen): The parent protein from which TINAGL1 (TINAG-Like 1) is derived

  • These proteins share structural features and may have overlapping functions

• Functional equivalents:

  • Other secreted proteins that interact with integrin beta 1, such as fibronectin, laminin, and certain collagens

  • Matricellular proteins (e.g., thrombospondins, osteopontin) that also modulate cell-matrix interactions

• Pathway components:

  • Integrin beta 1 and its alpha subunit partners

  • FAK and downstream signaling components

  • Other proteins involved in focal adhesion formation and turnover

• Contextual proteins:

  • For cancer studies: Other CAF-secreted factors that may work in concert with TINAGL1

  • ECM components that co-localize with TINAGL1 (e.g., COL1A1)

Including these related proteins as controls or comparative factors in experimental designs can provide important context for understanding TINAGL1's specific roles and can help distinguish unique versus redundant functions .

How can systems biology approaches enhance our understanding of TINAGL1's role in complex biological networks?

Systems biology approaches offer powerful frameworks for understanding TINAGL1's role in complex biological networks:

• Network analysis:

  • Integration of protein-protein interaction data can position TINAGL1 within broader signaling networks

  • Identification of hub proteins that connect TINAGL1 to different cellular processes

  • Detection of feedback loops and regulatory mechanisms

• Multi-omics integration:

  • Combining transcriptomics, proteomics, and metabolomics data to understand how TINAGL1 affects multiple cellular systems

  • Correlation of TINAGL1 expression with global changes in gene and protein expression patterns

  • Identification of potential biomarkers that co-occur with TINAGL1 expression

• Mathematical modeling:

  • Development of computational models to predict the effects of TINAGL1 perturbation on cellular behavior

  • Simulation of dose-response relationships and temporal dynamics

  • Testing hypotheses in silico before experimental validation

• Pathway enrichment analysis:

  • Identification of biological pathways significantly associated with TINAGL1 expression or activity

  • Discovery of unexpected connections to cellular processes not previously linked to TINAGL1

• Network pharmacology:

  • Prediction of drugs that might modulate TINAGL1-associated pathways

  • Identification of potential drug targets within TINAGL1-related networks

These approaches can reveal emergent properties and system-level effects that might not be apparent from reductionist approaches focusing solely on TINAGL1 .

What bioinformatic resources and tools are most valuable for TINAGL1 researchers?

Several bioinformatic resources and tools are particularly valuable for TINAGL1 researchers:

• Protein structure and function prediction:

  • AlphaFold/RoseTTAFold: For prediction of TINAGL1's three-dimensional structure

  • ConSurf: For identification of evolutionarily conserved regions

  • ProFunc: For prediction of functional sites

• Expression databases:

  • The Cancer Genome Atlas (TCGA): For examining TINAGL1 expression across cancer types

  • GTEx: For analyzing expression in normal tissues

  • Human Protein Atlas: For protein-level expression data across tissues

• Interaction databases:

  • STRING: For protein-protein interaction networks

  • Human Integrated Protein-Protein Interaction Reference (HIPIE): For high-confidence interaction data

  • IntAct: For experimentally validated molecular interactions

• Pathway analysis tools:

  • REACTOME: For pathway enrichment analysis

  • KEGG: For metabolic and signaling pathway mapping

  • g:Profiler: For functional profiling of gene lists

• Regulatory network analysis:

  • ENCODE: For transcription factor binding and chromatin state information

  • miRNet: For miRNA-target gene interactions

  • NetworkAnalyst: For constructing regulatory networks

• Clinical correlation tools:

  • cBioPortal: For exploring cancer genomics datasets and survival correlations

  • Kaplan-Meier Plotter: For survival analysis based on gene expression

These resources can help researchers contextualize their experimental findings, generate new hypotheses, and identify potential clinical implications of their TINAGL1 research .

How might computational approaches aid in designing inhibitors or modulators of TINAGL1 function?

Computational approaches offer powerful methods for designing inhibitors or modulators of TINAGL1 function:

• Structure-based drug design:

  • Virtual screening of compound libraries against binding pockets on TINAGL1's structure

  • Molecular docking to predict binding modes and affinities

  • Structure-activity relationship (SAR) analysis to optimize lead compounds

• Fragment-based approaches:

  • Identification of small molecular fragments that bind to different regions of TINAGL1

  • Computational linking of fragments to design higher-affinity compounds

  • Growing fragments into larger molecules with improved properties

• Peptide mimetics:

  • Design of peptides that mimic the binding interface between TINAGL1 and its receptors

  • Optimization for stability, bioavailability, and target selectivity

  • Computational prediction of peptide structure and binding

• Molecular dynamics simulations:

  • Analysis of TINAGL1's dynamic behavior and conformational changes

  • Identification of transient binding pockets not visible in static structures

  • Prediction of how mutations or ligand binding affects protein dynamics

• Machine learning approaches:

  • Training models on existing protein-ligand interaction data

  • Prediction of novel compounds likely to interact with TINAGL1

  • Optimization of multiple parameters simultaneously (activity, selectivity, ADME properties)

• Network-based drug discovery:

  • Identification of nodes in TINAGL1-associated networks that could be targeted

  • Prediction of combination therapies that might synergize with TINAGL1 inhibition

These computational approaches can accelerate the drug discovery process by prioritizing compounds for experimental testing and providing mechanistic insights into inhibitor binding and function .